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April 16, 2008

The Semantic Arms Race: Facebook vs. Google

As I discussed in Over $100m in 12 months backs natural language for the semantic web, Radar Networks’ Twine is one of the more interesting semantic web startups.  Their founder, Nova Spivak, is funded by Vulcan and others to provide “interest-driven [social] networking”.  I’ve been participating in the beta program at modest bandwidth for a while.  Generally, Nova’s statements about where they are and where they are going are fully supported by what I have experienced.  There are obvious weaknesses that they are improving.  Overall, the strategy of gradually bootstrapping functionality and content by controlling the ramp up in users from a clearly alpha stage implementation to what is still not quite beta (in my view) seems perfect. 

Recently, Nova recorded a few minute video in which he makes three short-term predictions:More...

  1. Yahoo’s indexing of RDF will start the Semantic Web 3.0 arms race involving Google and Microsoft.
  2. The web will transition from pages to linked data. 
  3. Facebook “has to compete” with Google.

Nova was a little on the spot in the video.  Personally, I liked his “the web becomes a database” comment more than the Berners-Lee reiteration of linked data.  The notion of the entire web being a database is the right perspective on the semantic web (i.e., RDF), in my view.  Linked data is boring (try the Tabulator if linked data excites you.)  The action (and opportunity) is doing something with it!  When asked about ten years out, Nova displayed more of his deep insight and vision, however.  (See below.)  The truth is, beyond his first one, Nova was a little on the spot.  (See for yourself in the video.)

I love the pithy #3 that he decided to throw in there.  He did not invent that on the spot but found his legs just before being asked about longer term vision.   It makes sense, of course.  Google’s attacking with Open Social (so is the rest of the world including all the bookmarkers and even Nova’s Twine).  Facebook has to shift direction and the only target big enough given its size is search and advertising.

In his longer term vision he mentions the intelligent web that reasons and helps make decisions.  

This is where the battleground is for artificial intelligence and Semantic Web 4.0 (his term for the 4th decade of the web starting circa 2020).

Personally, I think natural language should have been in his first three.  Powerset will demonstrate that and all the action around Reuter/Clearforest/Calais (which he mentions and expects Google to compete with) indicate that natural language is critical to populating the semantic web (of course we have the database approach of DBpedia and Freebase, too).  In general, people are not going tag sentences or paragraphs.  Machines will.  The only RDF people are going to add are meta-tags at the page level for search engine optimization given Yahoo’s move (and the expected response from Google that Nova mentions.)

Certainly, natural language understanding is a prerequisite for the Semantic Web 4.0.  We will be talking more and typing less long before then.

Learning from the Future with Nova Spivack from Maarten on Vimeo.

March 28, 2008

Harvesting business rules from the IRS

Does your business have logic that is more or less complicated than filing your taxes?

Most business logic is at least as complicated.  But most business rule metaphors are not up to expressing tax regulations in a simple manner.  Nonetheless, the tax regulations are full of great training material for learning how to analyze and capture business rules.

For example, consider the earned income credit (EIC) for federal income tax purposes in the United States.  This tutorial uses the guide for 2003, which is available here. There is also a cheat sheet that attempts to simplify the matter, available here. (Or click on the pictures.)

eitc-publication-596-fy-2003.jpgeitc-eligibility-checklist-for-tax-year-2003.jpg

What you will see here is typical of what business analysts do to clarify business requirements, policies, and logic.  Nothing here is specific to rule-based programming.  (more…)

March 20, 2008

RuleBurst Re-brands as Haley Limited

For those who are interested in my former company, they are still committed to natural language business rules management technology, as shown in their most recent press release.  They have also picked up on the public sector activity, especially eligibility, as discussed here

From the release, CEO, Dominic OHanlon, said:

  • “With our natural language rule authoring capabilities and BRMS solutions, we are uniquely positioned to make our customers more competitive and agile in a fast-paced, highly-regulated world.”
  • “For the government market, Haley is a worldwide leader in using natural language technology to rapidly transform regulations, policies and rules into automated decision-making systems, to determine eligibility for government services, and in the taxation and immigration arenas.”

As discussed here, this focuses comes from (more…)

January 31, 2008

The $50 Business Rule

Work on acquiring knowledge about science has estimated the cost of encoding knowledge in question answering or problem solving systems at $10,000 per page of relevant textbooks.  Regrettably, such estimates are also consistent with the commercial experience of many business rules adopters.  The cost of capturing and automating hundreds or thousands of business rules is typically several hundred dollars per rule.  The labor costs alone for a implementing several hundred rules too often exceed $100,000.

The fact that most rule adopters face costs exceeding $200 per rule is even more discouraging when this cost does not include the cost of eliciting or harvesting functional requirements or policies but is just the cost of translating such content into the more technical expressions understood by business rules management systems (BRMS) or business rule engines (BRE).

I recommend against adopting any business rule approach that cannot limit the cost of automating elicited or harvested content to less than $100 per rule given a few hundred rules.  In fact, Automata provides fixed price services consistent with the following graph using an approach similar to the one I developed at Haley Systems.

Cost per Harvested or Elicited Rule

(more…)

January 8, 2008

Elicitation and Management of Rules, Requirements and Decisions

A manager of an enterprise architecture group recently asked me how to train business analysts to elicit or harvest rules effectively. We talked for a bit about the similarities in skills between rules and requirements and agreed that analysts will fail to understand rules as they fail to understand requirements.

For example, just substitute rules in the historical distribution of requirements failures:[1]

  • 34% Incorrect requirements
  • 24% Inadequate requirements
  • 22% Ambiguous requirements
  • 9% Inconsistent requirements
  • 4% Poor scoping of requirements
  • 4% Transcription errors in requirements
  • 3% New or changing requirements

(more…)

December 11, 2007

Managing Semantics, Vocabulary and Business Rules as Knowledge

A client recently asked me for guidance in establishing a center of excellence concerning business rules within their organization. Their objectives included:

  1. Accumulate requisite skills for productive success.
  2. Establish methodologies for productive, reliable and repeatable success.
  3. Accumulate and reuse content (e.g., definitions, requirements, regulations, and policies) across implementations, departments or divisions.
  4. Establish multiple tutorial and reusable reference implementations, including application development, tooling, and integration aspects.
  5. Establish centralized or transferable infrastructure, including architectural aspects, tools and repositories that reflect and support established methodologies, reusable content, and reference implementations.
  6. Establish criteria, best practices and rationale for various administrative matters, especially change management concerning the life cycles of content (e.g., regulations or policies) and applications (e.g., releases and patches).

I was quickly surprised to find myself struggling to write down recommendations for the skill set required to seed the core staff.  My recommendations were less technical than the client may have expected.   After further consideration, it became clear than any discrepancy in expectations arose from differences in our unvoiced strategic assumptions.  Objectives, such as those listed above, are no substitute for a clearly articulated mission and strategy.  

(more…)

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